Welcome to this massive open online course (MOOC) about Qualitative Comparative Analysis (QCA). Please read the points below before you start the course. This will help you prepare well for the course and attend it properly. It will also help you determine if the course offers the knowledge and skills you are looking for.
What can you do with QCA?
• QCA is a comparative method that is mainly used in the social sciences for the assessment of cause-effect relations (i.e. causation).
• QCA is relevant for researchers who normally work with qualitative methods and are looking for a more systematic way of comparing and assessing cases.
• QCA is also useful for quantitative researchers who like to assess alternative (more complex) aspects of causation, such as how factors work together in producing an effect.
• QCA can be used for the analysis of cases on all levels: macro (e.g. countries), meso (e.g. organizations) and micro (e.g. individuals).
• QCA is mostly used for research of small- and medium-sized samples and populations (10-100 cases), but it can also be used for larger groups. Ideally, the number of cases is at least 10. QCA cannot be used if you are doing an in-depth study of one case.
What will you learn in this course?
• The course is designed for people who have no or little experience with QCA.
• After the course you will understand the methodological foundations of QCA.
• After the course you will know how to conduct a basic QCA study by yourself.
How is this course organized?
• The MOOC takes five weeks. The specific learning objectives and activities per week are mentioned in appendix A of the course guide. Please find the course guide under Resources in the main menu.
• The learning objectives with regard to understanding the foundations of QCA and practically conducting a QCA study are pursued throughout the course. However, week 1 focuses more on the general analytic foundations, and weeks 2 to 5 are more about the practical aspects of a QCA study.
• The activities of the course include watching the videos, consulting supplementary material where necessary, and doing assignments. The activities should be done in that order: first watch the videos; then consult supplementary material (if desired) for more details and examples; then do the assignments.
• There are 10 assignments. Appendix A in the course guide states the estimated time needed to make the assignments and how the assignments are graded. Only assignments 1 to 6 and 8 are mandatory. These 7 mandatory assignments must be completed successfully to pass the course.
• Making the assignments successfully is one condition for receiving a course certificate. Further information about receiving a course certificate can be found here: https://learner.coursera.help/hc/en-us/articles/209819053-Get-a-Course-Certificate
About the supplementary material
• The course can be followed by watching the videos. It is not absolutely necessary yet recommended to study the supplementary reading material (as mentioned in the course guide) for further details and examples. Further, because some of the covered topics are quite technical (particularly topics in weeks 3 and 4 of the course), we provide several worked examples that supplement the videos by offering more specific illustrations and explanation. These worked examples can be found under Resources in the main menu.
• Note that the supplementary readings are mostly not freely available. Books have to be bought or might be available in a university library; journal publications have to be ordered online or are accessible via a university license.
• The textbook by Schneider and Wagemann (2012) functions as the primary reference for further information on the topics that are covered in the MOOC. Appendix A in the course guide mentions which chapters in that book can be consulted for which week of the course.
• The publication by Schneider and Wagemann (2012) is comprehensive and detailed, and covers almost all topics discussed in the MOOC. However, for further study, appendix A in the course guide also mentions some additional supplementary literature.
• Please find the full list of references for all citations (mentioned in this course guide, in the MOOC, and in the assignments) in appendix B of the course guide.

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Using FsQCA, more about the interpretation of output, and the write-up

In week 5, it will be demonstrated how a) software can be used for making the truth table and performing logical minimization. We will also further discuss b) the interpretation of the results of logical minimization and c) the reporting of results of a QCA study in a scientifically sound manner.

Enseigné par

Fadi Hirzalla

Assistant Professor / Senior Lecturer

Transcription

Welcome everyone. Welcome to the fifth and last week of this course about QCA. The first two lectures of this week focus on using software to conduct a QCA allowances. The third lecture discusses the write-up of a QCA study. The software that we will discuss can be used for all major analytic steps which is convenient and practical as doing all the analysis manually is time consuming. There are different software packages you can use. TOSMANA and FsQCA are the two most widely used programs. In this lecture, I will show you how to use the program FsQCA version 3.0. I will use the Windows version of the program, but the Mac version is not very different. My explanation will be relevant for both fuzzy and crisp set QCA, although FsQC stands for fuzzy set QC, you can use the program for both for both fuzzy and crisp sets. Now there are three main steps that we will discuss as regard to the use of FsQCA. It starts with uploading a data matrix. Then you make the truth table. Lastly you minimize the truth table. In this lecture, we will discuss the part that is shown in red, uploading a data matrix and making the truth table. As regards making the truth table, We will discuss only how the program distinguishes between truth table rows or configurations, and the assigns cases to each row. These are as discussed in week three, the first two steps of making a truth table. The analysis starts with uploading a data matrix. To do that you go to file. Click "Open" and then you can select a data matrix from your browser. Data matrices need to be saved in a specific format before you can upload them. The required format is described in the manual of the program, which is mentioned in this week's reading list. As an example, I will select a data-set of a study by Downey Stanyer from 2014. It appears in the left side of the main window. You can see the conditions and the outcome in the columns, and the cases are in the rows. In this study, the authors wanted to explain why media publicize politicians' infidelity. So, publicize infidelity denoted with PubINF is their outcome. The oldest expected that this publicizing fidelity can be explained by five conditions including; low party, identification among voters or LPI. The presence of a tabloid media sector or TAB, and weak privacy protection or WPP. They investigated the outcome and these conditions in eight different countries. If you want to know more about the study, check the literature list of this course and find the full reference for the study by Downy Stanyer from 2014. In the second step of using the program, you have to transform the data matrix into a truth table. To do that, you go to Analyze. Then you click on truth table algorithm. In the subsequent window you have to indicate the outcome via set, and you need to indicate the conditions via Add. You do this when you want to analyze which conditions lead to the presence of the outcome. To analyze the absence of the outcome, you will have to bring your outcome to the set negated button here to the outcome box. It's good to keep in mind that the analysis of the absence of the outcome is similar to the analysis of the presence of the outcome. So, while the outcome differs, the next steps in using the program stay the same. You can also ask the program to show you the cases for each row in the truth table. You can do that by clicking on show solution cases in output. Indicating which column in the data matrix contains the cases. Now, after you've indicated the outcome, the conditions, and the cases in your model. You can press, "OK" and then the truth table appears in a new window. You can see that the conditions are described in terms of zeros indicating absence, and one's indicating presence. Even though the data matrix here contained fuzzy data, the truth table only shows zeros and ones. Further, you can see that the program has distinguished between all possible configurations in the rows. Which is the first step in making a truth table. The program has also assigned cases to each configuration, which is the second step of making a truth table. In this column, it indicates the number of cases for each truth table row, and between parenthesis, the cumulative percentage for each row. In this column, you can press on one of the buttons to see which cases are assigned to which rows. You can see that the third step of making a truth table which is defining the column with the outcome has not yet been taken. The truth table does not automatically mentioned in that column are one to indicate the sufficiency of a truth table row for the outcome or a zero for insufficiency. Instead you will need to define the outcome of each row based on the raw consistencies in this column. I will show you how you can do that in the next video. In the next video we'll also discuss the logical minimization. See you next time.